IDEAS home Printed from https://ideas.repec.org/a/gam/jagris/v13y2023i7p1303-d1179732.html
   My bibliography  Save this article

Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules

Author

Listed:
  • Zhengkai Wu

    (College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
    Hebei Intelligent Agricultural Equipment Technology Innovation Center, Baoding 071001, China)

  • Jiazhong Wang

    (College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
    Hebei Intelligent Agricultural Equipment Technology Innovation Center, Baoding 071001, China)

  • Yazhou Xing

    (College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
    Hebei Intelligent Agricultural Equipment Technology Innovation Center, Baoding 071001, China)

  • Shanshan Li

    (College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
    Hebei Intelligent Agricultural Equipment Technology Innovation Center, Baoding 071001, China)

  • Jinggang Yi

    (College of Mechanical and Electrical Engineering, Agricultural University of Hebei, Baoding 071001, China
    Hebei Intelligent Agricultural Equipment Technology Innovation Center, Baoding 071001, China)

  • Chunming Zhao

    (Tianjin Yidingfeng Power Technology Co., Ltd., Tianjin 300380, China)

Abstract

In order to ensure the continuity and endurance mileage requirements during sowing operations, it is necessary to establish accurate modeling for the working condition of the electric tractor sowing unit by adopting a reasonable energy management strategy and realizing accurate energy prediction. The existing electric tractor sowing unit battery energy management strategy is not optimal since it is mostly based on extensive rules. In this paper, according to the requirements of the sowing conditions, a precise model of electric energy consumption in the sowing cycle was established and an energy management strategy of sowing unit of extended-range electric tractor with power CD-CS was proposed. Fuzzy control rules of the dynamic SOC correction factor were established in the battery maintenance stage, and the NSGA-II algorithm was used to optimize the fuzzy control rules to optimize the battery charging and discharging efficiency. A hardware-in-the-loop simulation test platform was built, and the proposed CD-CS strategy was compared with the fuzzy improvement strategy. The simulation results show that the proposed fuzzy improvement strategy extended the battery life of the power consumption stage by 2131.9 s, which is a significant improvement. The field practical results showed that the SOC decreased by 7.21% and the simulation by 4.94% in terms of power consumption in a cycle. The power consumption variance was within a reasonable range, which further verifies the feasibility of the strategy.

Suggested Citation

  • Zhengkai Wu & Jiazhong Wang & Yazhou Xing & Shanshan Li & Jinggang Yi & Chunming Zhao, 2023. "Energy Management of Sowing Unit for Extended-Range Electric Tractor Based on Improved CD-CS Fuzzy Rules," Agriculture, MDPI, vol. 13(7), pages 1-18, June.
    • Handle: RePEc:gam:jagris:v:13:y:2023:i:7:p:1303-:d:1179732
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2077-0472/13/7/1303/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2077-0472/13/7/1303/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Yao Yu & Shuaihua Hao & Songbao Guo & Zhong Tang & Shuren Chen, 2022. "Motor Torque Distribution Strategy for Different Tillage Modes of Agricultural Electric Tractors," Agriculture, MDPI, vol. 12(9), pages 1-22, September.
    2. Meng Yang & Xiaoxu Sun & Xiaoting Deng & Zhixiong Lu & Tao Wang, 2023. "Extrapolation of Tractor Traction Resistance Load Spectrum and Compilation of Loading Spectrum Based on Optimal Threshold Selection Using a Genetic Algorithm," Agriculture, MDPI, vol. 13(6), pages 1-20, May.
    3. Zhang, Sheng-li & Wen, Chang-kai & Ren, Wen & Luo, Zhen-hao & Xie, Bin & Zhu, Zhong-xiang & Chen, Zhong-ju, 2023. "A joint control method considering travel speed and slip for reducing energy consumption of rear wheel independent drive electric tractor in ploughing," Energy, Elsevier, vol. 263(PD).
    4. Shen, Peihong & Zhao, Zhiguo & Zhan, Xiaowen & Li, Jingwei & Guo, Qiuyi, 2018. "Optimal energy management strategy for a plug-in hybrid electric commercial vehicle based on velocity prediction," Energy, Elsevier, vol. 155(C), pages 838-852.
    5. Zhen Zhu & Yanpeng Yang & Dongqing Wang & Yingfeng Cai & Longhui Lai, 2022. "Energy Saving Performance of Agricultural Tractor Equipped with Mechanic-Electronic-Hydraulic Powertrain System," Agriculture, MDPI, vol. 12(3), pages 1-22, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Zhenhao Luo & Jihang Wang & Jing Wu & Shengli Zhang & Zhongju Chen & Bin Xie, 2023. "Research on a Hydraulic Cylinder Pressure Control Method for Efficient Traction Operation in Electro-Hydraulic Hitch System of Electric Tractors," Agriculture, MDPI, vol. 13(8), pages 1-18, August.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Francesco Mocera & Aurelio Somà & Salvatore Martelli & Valerio Martini, 2023. "Trends and Future Perspective of Electrification in Agricultural Tractor-Implement Applications," Energies, MDPI, vol. 16(18), pages 1-36, September.
    2. Li, Xianzhe & Liu, Mengnan & Hu, Chenming & Yan, Xianghai & Zhao, Sixia & Zhang, Mingzhu & Xu, Liyou, 2024. "Parameters collaborative optimization design and innovation verification approach for fuel cell distributed drive electric tractor," Energy, Elsevier, vol. 292(C).
    3. Ku, Donggyun & Choi, Minje & Yoo, Nakyoung & Shin, Seungheon & Lee, Seungjae, 2021. "A new algorithm for eco-friendly path guidance focused on electric vehicles," Energy, Elsevier, vol. 233(C).
    4. Md. Abu Ayub Siddique & Seung-Yun Baek & Seung-Min Baek & Hyeon-Ho Jeon & Jun-Ho Lee & Mo-A Son & Su-Young Yoon & Yong-Joo Kim & Ryu-Gap Lim, 2023. "The Selection of an Energy-Saving Engine Mode Based on the Power Delivery and Fuel Consumption of a 95 kW Tractor during Rotary Tillage," Agriculture, MDPI, vol. 13(7), pages 1-16, July.
    5. Yang, Jibin & Xu, Xiaohui & Peng, Yiqiang & Zhang, Jiye & Song, Pengyun, 2019. "Modeling and optimal energy management strategy for a catenary-battery-ultracapacitor based hybrid tramway," Energy, Elsevier, vol. 183(C), pages 1123-1135.
    6. Taghavifar, Hadi, 2021. "Fuel cell hybrid range-extender vehicle sizing: Parametric power optimization," Energy, Elsevier, vol. 229(C).
    7. Wu, Yuankai & Tan, Huachun & Peng, Jiankun & Zhang, Hailong & He, Hongwen, 2019. "Deep reinforcement learning of energy management with continuous control strategy and traffic information for a series-parallel plug-in hybrid electric bus," Applied Energy, Elsevier, vol. 247(C), pages 454-466.
    8. Zhenhao Luo & Jihang Wang & Jing Wu & Shengli Zhang & Zhongju Chen & Bin Xie, 2023. "Research on a Hydraulic Cylinder Pressure Control Method for Efficient Traction Operation in Electro-Hydraulic Hitch System of Electric Tractors," Agriculture, MDPI, vol. 13(8), pages 1-18, August.
    9. Chengliang Zhang & Changpu Li & Chunzhao Zhao & Lei Li & Guanlei Gao & Xiyuan Chen, 2022. "Design of Hydrostatic Chassis Drive System for Large Plant Protection Machine," Agriculture, MDPI, vol. 12(8), pages 1-16, July.
    10. Wang, Shuai & Wu, Xiuheng & Zhao, Xueyan & Wang, Shilong & Xie, Bin & Song, Zhenghe & Wang, Dongqing, 2023. "Co-optimization energy management strategy for a novel dual-motor drive system of electric tractor considering efficiency and stability," Energy, Elsevier, vol. 281(C).
    11. Yang, Chao & Wang, Muyao & Wang, Weida & Pu, Zesong & Ma, Mingyue, 2021. "An efficient vehicle-following predictive energy management strategy for PHEV based on improved sequential quadratic programming algorithm," Energy, Elsevier, vol. 219(C).
    12. Zhang, LiPeng & Liu, Wei & Qi, BingNan, 2020. "Energy optimization of multi-mode coupling drive plug-in hybrid electric vehicles based on speed prediction," Energy, Elsevier, vol. 206(C).
    13. López-Ibarra, Jon Ander & Gaztañaga, Haizea & Saez-de-Ibarra, Andoni & Camblong, Haritza, 2020. "Plug-in hybrid electric buses total cost of ownership optimization at fleet level based on battery aging," Applied Energy, Elsevier, vol. 280(C).
    14. Zhang, Hanyu & Du, Lili, 2023. "Platoon-centered control for eco-driving at signalized intersection built upon hybrid MPC system, online learning and distributed optimization part I: Modeling and solution algorithm design," Transportation Research Part B: Methodological, Elsevier, vol. 172(C), pages 174-198.
    15. Shi, Wenzhuo & Huangfu, Yigeng & Xu, Liangcai & Pang, Shengzhao, 2022. "Online energy management strategy considering fuel cell fault for multi-stack fuel cell hybrid vehicle based on multi-agent reinforcement learning," Applied Energy, Elsevier, vol. 328(C).
    16. Zhang, Yuanjian & Chu, Liang & Fu, Zicheng & Xu, Nan & Guo, Chong & Zhao, Di & Ou, Yang & Xu, Lei, 2020. "Energy management strategy for plug-in hybrid electric vehicle integrated with vehicle-environment cooperation control," Energy, Elsevier, vol. 197(C).
    17. Wang, Yue & Zeng, Xiaohua & Song, Dafeng, 2020. "Hierarchical optimal intelligent energy management strategy for a power-split hybrid electric bus based on driving information," Energy, Elsevier, vol. 199(C).
    18. Vu, Ngoc-Lam & Messier, Pascal & Nguyễn, Bảo-Huy & Vo-Duy, Thanh & Trovão, João Pedro F. & Desrochers, Alain & Rodrigues, António, 2023. "Energy-optimization design and management strategy for hybrid electric non-road mobile machinery: A case study of snowblower," Energy, Elsevier, vol. 284(C).
    19. Weijian Liu & Xiwen Luo & Shan Zeng & Li Zeng & Zhiqiang Wen, 2022. "The Design and Test of the Chassis of a Triangular Crawler-Type Ratooning Rice Harvester," Agriculture, MDPI, vol. 12(6), pages 1-17, June.
    20. Wang, Yue & Li, Keqiang & Zeng, Xiaohua & Gao, Bolin & Hong, Jichao, 2023. "Investigation of novel intelligent energy management strategies for connected HEB considering global planning of fixed-route information," Energy, Elsevier, vol. 263(PB).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jagris:v:13:y:2023:i:7:p:1303-:d:1179732. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.